• 제목/요약/키워드: approximate algorithm

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다층 신경회로망을 이용한 비선형 시스템의 견실한 제어 (Robust control of nonlinear system using multilayer neural network)

  • 성홍석;이쾌희
    • 전자공학회논문지S
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    • 제34S권9호
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    • pp.41-49
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    • 1997
  • In this paper, we describe the algorithm which controls an unknown nonlinear system with disturbance a using multilayer neural network. The multilayer neural network can be used to approximate any continuous function to any desired degree of accuracy. With the former fact, we approximate an unknown nonlinear system by using of multilayer neural netowrk. WE include a disturbance among the modelling error, and the weight-update rule of multilayer neural network is derived to satisfy Laypunov stability. The whole control system constitutes controller using the feedback linearization method. The weight of neural network which is used to implement nonlinear function is updated by the derived update-rule. The proposed control algorithm is verified through computer simulation.

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A PRECONDITIONER FOR THE NORMAL EQUATIONS

  • Salkuyeh, Davod Khojasteh
    • Journal of applied mathematics & informatics
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    • 제28권3_4호
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    • pp.687-696
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    • 2010
  • In this paper, an algorithm for computing the sparse approximate inverse factor of matrix $A^{T}\;A$, where A is an $m\;{\times}\;n$ matrix with $m\;{\geq}\;n$ and rank(A) = n, is proposed. The computation of the inverse factor are done without computing the matrix $A^{T}\;A$. The computed sparse approximate inverse factor is applied as a preconditioner for solving normal equations in conjunction with the CGNR algorithm. Some numerical experiments on test matrices are presented to show the efficiency of the method. A comparison with some available methods is also included.

신경회로망을 이용한 비선형 시스템 제어 (Nonlinear system control using neural network)

  • 성홍석;이쾌희
    • 전자공학회논문지B
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    • 제33B권7호
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    • pp.32-39
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    • 1996
  • In this paper, we describe the algorithm which controls an unknown nonlinear system with multilayer neural network. The multilayer neural netowrk can be used to approximate any continuous function to any desired degree of accuracy. With the former fact, we approximate unknown nonlinear function on the nonlinear system by using of multilayer neural netowrk. The weights on the hidden layer of multilayer neural network are updated by gradient method. The weight-update rule on the output layer is derived to satisfy lyapunov stability. Also, we obtain secondary controller form deriving step. The global control system consists of controller using feedback linearization method and secondary controller is order to satisfy layapunov stability. The proposed control algorithm is verified through computer simulation.

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예조건화된 압축성유동 수치기법에서의 풍상차분법의 수치특성 검토 (Numerical Characteristics of Upwind Schemes for Preconditioned Compressible Navier-Stokes Equations)

  • 길재흥;이두환;최윤호;권장혁;이승수
    • 한국전산유체공학회:학술대회논문집
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    • 한국전산유체공학회 2002년도 추계 학술대회논문집
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    • pp.95-102
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    • 2002
  • Studies of the numerical characteristics of implicit upwind schemes, such as upwind ADI, Line Gauss-Seidel(LGS) and Point Gauss-Seidel(LU) algorithms, for preconditioned Navier-Stokes equations ate performed. All the algorithms are expressed in approximate factorization form and Von Neumann stability analysis and convergence studies are made. Preconditioning is applied for efficient convergence at low Mach numbers and low Reynolds numbers. For high aspect ratio computations, the ADI and LGS algorithms show efficient and uniform convergence up to moderate aspect ratio if we adopt viscous preconditioning based on min- CFL/max- VNN time-step definition. The LU algorithm, on the other hand, shows serious deterioration in convergence rate as the grid aspect ratio increases. Computations for practical applications also verify these results.

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Finding approximate occurrence of a pattern that contains gaps by the bit-vector approach

  • Lee, In-Bok;Park, Kun-Soo
    • 한국생물정보학회:학술대회논문집
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    • 한국생물정보시스템생물학회 2003년도 제2차 연례학술대회 발표논문집
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    • pp.193-199
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    • 2003
  • The application of finding occurrences of a pattern that contains gaps includes information retrieval, data mining, and computational biology. As the biological sequences may contain errors, it is important to find not only the exact occurrences of a pattern but also approximate ones. In this paper we present an O(mnk$_{max}$/w) time algorithm for the approximate gapped pattern matching problem, where m is the length of the text, H is the length of the pattern, w is the word size of the target machine, and k$_{max}$ is the greatest error bound for subpatterns.

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지식 추상화와 의미 거리 접근법을 통합한 질의 완화 방법론 (Relaxing Queries by Combining Knowledge Abstraction and Semantic Distance Approach)

  • 신명근;박성혁;이우기;허순영
    • 한국경영과학회지
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    • 제32권1호
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    • pp.125-136
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    • 2007
  • The study on query relaxation which provides approximate answers has received attention. In recent years, some arguments have been made that semantic relationships are useful to present the relationships among data values and calculating the semantic distance between two data values can be used as a quantitative measure to express relative distance. The aim of this article is a hierarchical metricized knowledge abstraction (HiMKA) with an emphasis on combining data abstraction hierarchy and distance measure among data values. We propose the operations and the query relaxation algorithm appropriate to the HiMKA. With various experiments and comparison with other method, we show that the HiMKA is very useful for the quantified approximate query answering and our result is to offer a new methodological framework for query relaxation.

무작위 데이터 근사화를 위한 유계오차 B-스플라인 근사법 (An Error-Bounded B-spline Fitting Technique to Approximate Unorganized Data)

  • 박상근
    • 한국CDE학회논문집
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    • 제17권4호
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    • pp.282-293
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    • 2012
  • This paper presents an error-bounded B-spline fitting technique to approximate unorganized data within a prescribed error tolerance. The proposed approach includes two main steps: leastsquares minimization and error-bounded approximation. A B-spline hypervolume is first described as a data representation model, which includes its mathematical definition and the data structure for implementation. Then we present the least-squares minimization technique for the generation of an approximate B-spline model from the given data set, which provides a unique solution to the problem: overdetermined, underdetermined, or ill-conditioned problem. We also explain an algorithm for the error-bounded approximation which recursively refines the initial base model obtained from the least-squares minimization until the Euclidean distance between the model and the given data is within the given error tolerance. The proposed approach is demonstrated with some examples to show its usefulness and a good possibility for various applications.

APPROXIMATE ANALYSIS OF AN N-DESIGN CALL CENTER WITH TWO TYPES OF AGENTS

  • Park, Chul-Geun;Han, Dong-Hwan;Baik, Kwang-Hyun
    • Journal of applied mathematics & informatics
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    • 제26권5_6호
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    • pp.1021-1035
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    • 2008
  • In this paper, we analyze an N-design call center with skill-based routing, in which one pool of agents handles two types of calls and another pool of agents handles only one type of calls. The approximate analysis is motivated by a computational complexity that has been observed in the direct stochastic approach and numerical method for finding performance measures. The workforce staffing policy is very important to the successful management of call centers. So the allocation scheduling of the agents can be considered as the optimization problem of the corresponding queueing system to the call center. We use a decomposition algorithm which divides the state space of the queueing system into the subspaces for the approximate analysis of the N-design call center with two different types of agents. We also represent some numerical examples and show the impact of the system parameters on the performance measures.

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클릭을 이용한 근사최소 부족수 순서화 (An Approximate Minimum Deficiency Ordering using Cliques)

  • 도승용;박찬규;이상욱;박순달
    • 한국경영과학회:학술대회논문집
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    • 한국경영과학회/대한산업공학회 2003년도 춘계공동학술대회
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    • pp.386-393
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    • 2003
  • For fast Cholesky factorization, it is most important to reduce the number of non-zero elements by ordering methods. Minimum deficiency ordering produces less non-zero elements. However, since it is very slow. the minimum degree algorithm is widely used. To improve the computation time, Rothberg's AMF uses an approximate deficiency instead of computing the deficiency. In this paper we present simple efficient methods to obtain a good approximate deficiency using information related to cliques. Experimental results show that our proposed method produces better ordering quality than that of AMF.

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Large-Scale TSP 근사해법에 관한 연구 (A Domain-Partition Algorithm for the Large-Scale TSP)

  • 유형선;김현승
    • 한국정밀공학회지
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    • 제9권3호
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    • pp.122-131
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    • 1992
  • In this paper an approximate solution method for the large-scale Traveling Salesman Problem (TSP) is presented. The method starts with the subdivision of the problem domain into a number of cluster by considering their geometric characteristic. Each cluster has a limited number of nodes so as to get a local solution. They are linked go give the least pathe which covers the whole domain and become TSPs solution with start-and end-node. The approximate local solution in each cluster are obtained based on geometrical properties of the cluster, and combined to give an overall approximate solution for the larte-scale TSP.

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